1. Field of the Invention
The present invention relates to an electroencephalograph (EEG) signal analysis system which determines, for very small increments of time, frequency values of EEG signals produced at various sites in response to a stimulus or task.
2. Description of the Prior Art
An electroencephalograph (EEG) is a device which measures and records brain wave activity by sensing electrical potential of a patient's scalp, cortex or cerebrum at various sites. Each EEG channel corresponds to a particular electrode combination attached to the patient. The sensed EEG potential at each channel is amplified by a differential amplifier, and the amplifier output signal is typically used to control movement of a recording pen of a polygraph. The EEG record is a long strip of polygraph paper containing a waveform for each EEG channel. The polygraph paper is driven at a predetermined rate (e.g. 30 millimeters per second) and is graduated to represent predetermined time increments. A neurologist must evaluate the EEG record to determine abnormalities in the EEG waveforms.
EEG signals exhibit different frequencies depending upon brain activity. The EEG signal frequencies are classified into four basic frequency bands, which are referred to as "delta" (0 to 3.5 Hertz); "theta" (4 to less than Hertz); "alpha" (8 to 13 Hertz); and "beta" (greater than 13 Hertz). The neurologist determines the predominant frequency of a particular channel during a particular time period by measuring the period of the EEG signal waveform shown on the EEG record. This requires considerable training and is highly dependent upon the skill of the neurologist, since the EEG signal waveform typically includes multiple frequency components.
In general, electronic equipment developed in the past for EEG analysis has been designed primarily for the acquisition of data, with little emphasis on the analysis of that data. Although computers were introduced into EEG technology in the early 1970's, there has been limited acceptance of computer-assisted EEG analysis due to a limited number of channels which are analyzed and a lack of an intuitive display. Existing computerized EEG technology has required a high degree of specialized knowledge to understand the information being displayed and, as a result, the market for that technology has been limited to a relatively small number of specialists in the field of electroencephalography.
One type of EEG signal analysis which has been performed by computers in the past has been called a "spectral analysis". In this type of analysis, the analog EEG signal for each channel is periodically sampled, converted to a digital value and stored. The stored digital data represents an EEG signal waveform (i.e. the amplitude of the EEG signal as a function of time). The computer converts the stored digital data from the time domain to the frequency domain by means of a Fast Fourier Transform (FFT) algorithm. The transformed data represents a frequency spectrum (i.e. amplitude or power of the EEG signal as a function of frequency). The computer provides the frequency spectrum as an output through some form of display.
The analysis of EEG signals in the frequency domain by use of a Fast Fourier Transform has, in the past, placed limits on the shortest time interval over which the EEG signals are sampled. The duration of the time interval determines the period of the lowest frequency in the frequency spectrum produced by the Fast Fourier Transform. Because the EEG signals have very low frequencies, the shortest time interval is typically one second (which corresponds to a lowest frequency of one Hertz). If a shorter time interval were selected, the lowest frequency which could be analyzed would be greater than one Hertz, and thus some or all of the frequencies of interest would be lost. For example, a time interval of twenty milliseconds would result in a lowest frequency of fifty Hertz. The nature of the Fast Fourier Transform and the low frequencies of the EEG signals, therefore, has limited the ability to analyze the frequency content of the EEG signals from various channels during very short time periods of interest.
Despite the development of EEG technology and despite years of study, much remains to be learned as to how the brain processes information. It is theorized that multiple areas of the brain process information in tandem under some type of common control, but the location or origin of that common control is not known. For instance, when a person hears a sound, it reaches the cortex in only about 10 milliseconds. People make decisions on what they have heard at about 60 to 70 milliseconds. These decisions are apparently arrived at after cortical processing, but in the past it has not been possible to determine where the cortical processing is occurring.
In the past, averaging techniques have been used to produce what is known as "Evoked Potentials". In these techniques, an auditory, visual or sensory stimulus is provided, and EEG signals are recorded over a period of time such as 400 to 500 milliseconds. The analog EEG signals are then converted to digital signals, and the digital signals from a series of identical tests are averaged in order to abolish "noise". After successive averaging, a digitized waveform is produced which represents average voltage as a function of time.
Because some of the "noise" which is eliminated by the averaging techniques is the result of cortical activity, the Evoked Potential waveform does not provide an indication of cortical frequency response as a function of time. It is known, however, that the frequency response from a particular portion of the brain does change in reference to use of that portion of the brain.
The frequency response of the cortex cannot be obtained using the Evoked Potential analysis, due to the averaging which is performed to produce the Evoked Potential waveforms. There are, however, cortical components that are seen in the Evoked Potential waveforms. These cortical components are widely distributed, although there is an increased amplitude over the site where they are first received within the cortex. In general, however, the cortical components are difficult to lateralize and hard to localize. The amplitude changes that are seen in the Evoked Potential waveform cannot be well equated with the amount of processing that occurs at that particular site. In fact, it is not even understood whether positivity or negativity of the Evoked Potential waveform means increased or decreased activity. For instance, it is known that if a subject pays attention to a particular sound stimulus, at about 100 milliseconds after that sound stimulus there is an increased negativity of the Evoked Potential waveforms. The significance of this negativity, its cause, or even its location in the cortex is not known.
There is a need for new techniques and equipment for analyzing EEG signals in such a way that a better understanding of the brain's processing of information can be obtained. In particular, there is a need for an EEG signal analyzer which will provide an indication of the frequency response of the cortex (and other structures) and which will demonstrate and record the processing activity of the brain in response to various stimulae or tasks performed.